diff --git "a/Source Code/Convergence/IMPACT-P ANN.ipynb" "b/Source Code/Convergence/IMPACT-P ANN.ipynb"
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+++ "b/Source Code/Convergence/IMPACT-P ANN.ipynb"
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+{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[],"collapsed_sections":["_T8fPo2P6CFY"]},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"}},"cells":[{"cell_type":"code","execution_count":1,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"AEp-GngME9rE","executionInfo":{"status":"ok","timestamp":1777438447776,"user_tz":-420,"elapsed":21049,"user":{"displayName":"all Penelitian","userId":"10978130364565931227"}},"outputId":"3600c744-9395-447b-c77f-997aa5a1fb16"},"outputs":[{"output_type":"stream","name":"stdout","text":["Collecting ijson\n","  Downloading ijson-3.5.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl.metadata (23 kB)\n","Downloading ijson-3.5.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl (149 kB)\n","\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m149.7/149.7 kB\u001b[0m \u001b[31m5.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[?25hInstalling collected packages: ijson\n","Successfully installed ijson-3.5.0\n"]}],"source":["!pip install ijson"]},{"cell_type":"code","source":["from google.colab import drive\n","drive.mount('/content/drive')"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"Cbi9HIU2YNKA","executionInfo":{"status":"ok","timestamp":1777438482095,"user_tz":-420,"elapsed":34304,"user":{"displayName":"all Penelitian","userId":"10978130364565931227"}},"outputId":"3bbd6a06-acd2-486c-c2a9-1ac1662f54d7"},"execution_count":2,"outputs":[{"output_type":"stream","name":"stdout","text":["Mounted at /content/drive\n"]}]},{"cell_type":"code","source":["import json\n","import gzip\n","import ast"],"metadata":{"id":"AeFl8khUG2Wz","executionInfo":{"status":"ok","timestamp":1777438482096,"user_tz":-420,"elapsed":9,"user":{"displayName":"all Penelitian","userId":"10978130364565931227"}}},"execution_count":3,"outputs":[]},{"cell_type":"markdown","source":["## Recommendation"],"metadata":{"id":"-s3p5tlhopND"}},{"cell_type":"markdown","source":["#### With tags and specifications"],"metadata":{"id":"eFg-8moUb52J"}},{"cell_type":"code","source":["import numpy as np\n","\n","user_tags_and_specs_features = np.load('/content/drive/MyDrive/Research/Disertation/Telkom University Artefak/02 Proposal/02 SOTA Bundle Matching (Feature Engineering Improve Relevance and Diversity)/Processing Data/user_tags_and_specs_features.npy')\n","user_tags_and_specs_label = np.load('/content/drive/MyDrive/Research/Disertation/Telkom University Artefak/02 Proposal/02 SOTA Bundle Matching (Feature Engineering Improve Relevance and Diversity)/Processing Data/user_tags_and_specs_label.npy')"],"metadata":{"id":"Egw06Nzgb8g1","executionInfo":{"status":"ok","timestamp":1777438493980,"user_tz":-420,"elapsed":11889,"user":{"displayName":"all Penelitian","userId":"10978130364565931227"}}},"execution_count":4,"outputs":[]},{"cell_type":"code","source":["# prompt: Distribution on len user_tags_and_specs_features\n","\n","import matplotlib.pyplot as plt\n","\n","# Assuming user_tags_and_specs_features is already loaded as a NumPy array\n","\n","lengths = [len(x) for x in user_tags_and_specs_features]\n","\n","plt.hist(lengths, bins=50)  # Adjust the number of bins as needed\n","plt.xlabel('Length of user_tags_and_specs_features')\n","plt.ylabel('Frequency')\n","plt.title('Distribution of Lengths')\n","plt.show()\n","print(f\"The average length is {np.mean(lengths)}\")\n","print(f\"The median length is {np.median(lengths)}\")\n","print(f\"The standard deviation of length is {np.std(lengths)}\")\n","print(f\"The maximum length is {np.max(lengths)}\")\n","print(f\"The minimum length is {np.min(lengths)}\")\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":559},"id":"yJpD_1HALjO_","executionInfo":{"status":"ok","timestamp":1735287312801,"user_tz":-420,"elapsed":1396,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}},"outputId":"013d14e0-23b4-45d5-e0de-da2a8b0a36c9"},"execution_count":null,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 1 Axes>"],"image/png":"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\n"},"metadata":{}},{"output_type":"stream","name":"stdout","text":["The average length is 225.0\n","The median length is 225.0\n","The standard deviation of length is 0.0\n","The maximum length is 225\n","The minimum length is 225\n"]}]},{"cell_type":"code","source":["import numpy as np\n","import pandas as pd\n","import tensorflow as tf\n","import matplotlib.pyplot as plt\n","import os\n","from sklearn.model_selection import KFold\n","from sklearn.preprocessing import MinMaxScaler\n","from sklearn.metrics import accuracy_score\n","\n","# 1. LOAD DATA\n","X = user_tags_and_specs_features\n","y = user_tags_and_specs_label\n","scaler = MinMaxScaler()\n","X = scaler.fit_transform(X)\n","\n","# 2. SETUP\n","kf = KFold(n_splits=5, shuffle=True, random_state=42)\n","dir_path = '/content/drive/MyDrive/Research/Disertation/Telkom University Artefak/02 Proposal/02 SOTA Bundle Matching (Feature Engineering Improve Relevance and Diversity)/models/ann_model/'\n","os.makedirs(dir_path, exist_ok=True)\n","\n","# 3. TRAINING LOOP\n","fold_accuracies = []\n","best_history = None\n","\n","for fold, (train_idx, val_idx) in enumerate(kf.split(X, y)):\n","    X_train, X_val = X[train_idx], X[val_idx]\n","    y_train_fold, y_val_fold = y[train_idx], y[val_idx]\n","\n","    model = tf.keras.Sequential([\n","        tf.keras.layers.Dense(128, activation=\"relu\", input_shape=(X.shape[1],)),\n","        tf.keras.layers.Dense(256, activation=\"relu\"),\n","        tf.keras.layers.Dense(128, activation=\"relu\"),\n","        tf.keras.layers.Dense(1, activation=\"sigmoid\")\n","    ])\n","    # Pastikan metrics=['accuracy']\n","    model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])\n","\n","    # Train 20 epochs\n","    history = model.fit(X_train, y_train_fold, epochs=20, batch_size=128,\n","                        validation_data=(X_val, y_val_fold), verbose=0)\n","\n","    y_pred = (model.predict(X_val) > 0.5).astype(\"int32\")\n","    fold_accuracies.append(accuracy_score(y_val_fold, y_pred))\n","\n","    # Simpan history dari fold terakhir untuk plotting\n","    if fold == 4: best_history = history\n","\n","# 4. SAVE CONVERGENCE DATA (Accuracy Focus)\n","history_df = pd.DataFrame(best_history.history)\n","history_df.to_csv(os.path.join(dir_path, 'ann_tags_accuracy_convergence.csv'), index_label='epoch')\n","\n","# 5. HD PLOTTING (Accuracy vs Epochs)\n","plt.figure(figsize=(10, 6), dpi=300)\n","plt.plot(history_df['accuracy'], label='Training Accuracy', marker='o', linewidth=2)\n","plt.plot(history_df['val_accuracy'], label='Validation Accuracy', marker='s', linewidth=2)\n","plt.title('Accuracy Convergence: ANN (Tags & Specs)', fontsize=16, fontweight='bold')\n","plt.xlabel('Epochs', fontsize=14)\n","plt.ylabel('Accuracy', fontsize=14)\n","plt.legend(fontsize=12)\n","plt.grid(True, linestyle='--', alpha=0.7)\n","plt.savefig(os.path.join(dir_path, 'ann_tags_accuracy_convergence.pdf'), bbox_inches='tight', dpi=300)\n","plt.show()\n","\n","# 6. FINAL STABILITY OUTPUT\n","print(\"\\n--- STABILITY SUMMARY (ANN) ---\")\n","print(f\"Mean Accuracy: {np.mean(fold_accuracies):.4f}\")\n","print(f\"Std Dev: {np.std(fold_accuracies):.4f}\")\n","\n","# 7. SAVE MODEL\n","model.save(os.path.join(dir_path, 'best_ann_tags_model.keras'))\n","print(f\"\\nModel dan Data Convergence (Accuracy) berhasil disimpan.\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"qpcxK_8thvGV","executionInfo":{"status":"ok","timestamp":1777441488251,"user_tz":-420,"elapsed":343475,"user":{"displayName":"all Penelitian","userId":"10978130364565931227"}},"outputId":"42e1d460-454e-4147-b442-3e95ecba7dcf"},"execution_count":7,"outputs":[{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["/usr/local/lib/python3.12/dist-packages/keras/src/layers/core/dense.py:106: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead.\n","  super().__init__(activity_regularizer=activity_regularizer, **kwargs)\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["\u001b[1m1150/1150\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 2ms/step\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["/usr/local/lib/python3.12/dist-packages/keras/src/layers/core/dense.py:106: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead.\n","  super().__init__(activity_regularizer=activity_regularizer, **kwargs)\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["\u001b[1m1150/1150\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 2ms/step\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["/usr/local/lib/python3.12/dist-packages/keras/src/layers/core/dense.py:106: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead.\n","  super().__init__(activity_regularizer=activity_regularizer, **kwargs)\n"]},{"metadata":{"tags":null},"name":"stdout","output_type":"stream","text":["\u001b[1m1150/1150\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 2ms/step\n"]},{"metadata":{"tags":null},"name":"stderr","output_type":"stream","text":["/usr/local/lib/python3.12/dist-packages/keras/src/layers/core/dense.py:106: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead.\n","  super().__init__(activity_regularizer=activity_regularizer, **kwargs)\n"]},{"output_type":"stream","name":"stdout","text":["\u001b[1m1150/1150\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 2ms/step\n"]},{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.12/dist-packages/keras/src/layers/core/dense.py:106: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead.\n","  super().__init__(activity_regularizer=activity_regularizer, **kwargs)\n"]},{"output_type":"stream","name":"stdout","text":["\u001b[1m1150/1150\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 2ms/step\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 3000x1800 with 1 Axes>"],"image/png":"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STABILITY SUMMARY (ANN) ---\n","Mean Accuracy: 0.8733\n","Std Dev: 0.0021\n","\n","Model dan Data Convergence (Accuracy) berhasil disimpan.\n"]}]},{"cell_type":"code","source":["import joblib\n","import pandas as pd\n","import numpy as np\n","import tensorflow as tf\n","from sklearn.model_selection import KFold\n","from sklearn.model_selection import train_test_split\n","from sklearn.metrics import accuracy_score, classification_report\n","\n","# Load the saved model\n","with open('/content/drive/MyDrive/Projects/Disertation/SOTA Bundle Matching/models/tags_specifications/neural_networks_tags_specifications.pkl', 'rb') as file:\n","    loaded_model = joblib.load(file)\n","\n","# Split data into training and testing sets\n","X_train, X_test, y_train, y_test = train_test_split(user_tags_and_specs_features, user_tags_and_specs_label, test_size=0.2, random_state=42)\n","\n","# Now you can use the loaded_model to make predictions\n","# For example:\n","y_pred = loaded_model.predict(X_test)\n","y_pred = (y_pred > 0.5).astype(int)  # Convert probabilities to binary predictions (0 or 1)\n","y_pred = y_pred.flatten() # Flatten y_pred to a 1D array\n","\n","print(classification_report(y_test, y_pred))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"cdFS0AWac8Q4","executionInfo":{"status":"ok","timestamp":1734855843779,"user_tz":-420,"elapsed":6440,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}},"outputId":"db40b6ea-e2b3-4c19-9d57-d9936ea19682"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["\u001b[1m1150/1150\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 3ms/step\n","              precision    recall  f1-score   support\n","\n","           0       0.88      0.44      0.59     18645\n","           1       0.62      0.94      0.75     18147\n","\n","    accuracy                           0.69     36792\n","   macro avg       0.75      0.69      0.67     36792\n","weighted avg       0.75      0.69      0.67     36792\n","\n"]}]},{"cell_type":"markdown","source":["#### With price patterns"],"metadata":{"id":"FZMag36kctY2"}},{"cell_type":"code","source":["import numpy as np\n","\n","user_price_features = np.load('/content/drive/MyDrive/Research/Disertation/Telkom University Artefak/02 Proposal/02 SOTA Bundle Matching (Feature Engineering Improve Relevance and Diversity)/Processing Data/user_price_features.npy')\n","user_price_label = np.load('/content/drive/MyDrive/Research/Disertation/Telkom University Artefak/02 Proposal/02 SOTA Bundle Matching (Feature Engineering Improve Relevance and Diversity)/Processing Data/user_price_label.npy')"],"metadata":{"id":"nY0oy9x2cy8P","executionInfo":{"status":"ok","timestamp":1777442077868,"user_tz":-420,"elapsed":12067,"user":{"displayName":"all Penelitian","userId":"10978130364565931227"}}},"execution_count":8,"outputs":[]},{"cell_type":"code","source":["import numpy as np\n","import pandas as pd\n","import tensorflow as tf\n","import matplotlib.pyplot as plt\n","import os\n","from sklearn.model_selection import KFold\n","from sklearn.preprocessing import MinMaxScaler\n","from sklearn.metrics import accuracy_score\n","import joblib\n","\n","# 1. LOAD & SUBSAMPLE\n","X_full = user_price_features\n","y_full = user_price_label\n","sample_limit = 50000\n","X = X_full[:sample_limit]\n","y = y_full[:sample_limit]\n","print(f\"Using {len(X)} samples for ANN (Price) evaluation.\")\n","\n","# 2. PREPROCESSING\n","scaler = MinMaxScaler()\n","X = scaler.fit_transform(X)\n","\n","# 3. SETUP\n","kf = KFold(n_splits=5, shuffle=True, random_state=42)\n","dir_path = '/content/drive/MyDrive/Research/Disertation/Telkom University Artefak/02 Proposal/02 SOTA Bundle Matching (Feature Engineering Improve Relevance and Diversity)/models/ann_price/'\n","os.makedirs(dir_path, exist_ok=True)\n","\n","# 4. TRAINING LOOP\n","fold_accuracies = []\n","best_history = None\n","\n","for fold, (train_idx, val_idx) in enumerate(kf.split(X, y)):\n","    X_train, X_val = X[train_idx], X[val_idx]\n","    y_train_fold, y_val_fold = y[train_idx], y[val_idx]\n","\n","    model = tf.keras.Sequential([\n","        tf.keras.layers.Dense(128, activation=\"relu\", input_shape=(X.shape[1],)),\n","        tf.keras.layers.Dense(256, activation=\"relu\"),\n","        tf.keras.layers.Dense(128, activation=\"relu\"),\n","        tf.keras.layers.Dense(1, activation=\"sigmoid\")\n","    ])\n","    model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])\n","\n","    # Train 20 epochs\n","    history = model.fit(X_train, y_train_fold, epochs=20, batch_size=128,\n","                        validation_data=(X_val, y_val_fold), verbose=0)\n","\n","    y_pred = (model.predict(X_val) > 0.5).astype(\"int32\")\n","    fold_accuracies.append(accuracy_score(y_val_fold, y_pred))\n","\n","    # Simpan history dari fold terakhir untuk plotting\n","    if fold == 4: best_history = history\n","\n","# 5. SAVE CONVERGENCE DATA (Accuracy Focus)\n","history_df = pd.DataFrame(best_history.history)\n","history_df.to_csv(os.path.join(dir_path, 'ann_price_accuracy_convergence.csv'), index_label='epoch')\n","\n","# 6. HD PLOTTING (Accuracy)\n","plt.figure(figsize=(10, 6), dpi=300)\n","plt.plot(history_df['accuracy'], label='Training Accuracy', marker='o', linewidth=2)\n","plt.plot(history_df['val_accuracy'], label='Validation Accuracy', marker='s', linewidth=2)\n","plt.title('Convergence Analysis: ANN Accuracy (Price Patterns)', fontsize=16, fontweight='bold')\n","plt.xlabel('Epochs', fontsize=14)\n","plt.ylabel('Accuracy', fontsize=14)\n","plt.legend(fontsize=12)\n","plt.grid(True, linestyle='--', alpha=0.7)\n","plt.savefig(os.path.join(dir_path, 'ann_price_accuracy_convergence.pdf'), bbox_inches='tight', dpi=300)\n","plt.show()\n","\n","# 7. STABILITY SUMMARY\n","print(\"\\n--- STABILITY SUMMARY (ANN PRICE) ---\")\n","print(f\"Mean Accuracy: {np.mean(fold_accuracies):.4f}\")\n","print(f\"Std Dev: {np.std(fold_accuracies):.4f}\")\n","\n","# 8. SAVE MODEL & SCALER\n","model.save(os.path.join(dir_path, 'ann_price_model.keras'))\n","joblib.dump(scaler, os.path.join(dir_path, 'scaler.pkl'))\n","print(f\"\\nModel dan Data Convergence (Accuracy) berhasil disimpan.\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"twU-lTQPcvo8","executionInfo":{"status":"ok","timestamp":1777442453882,"user_tz":-420,"elapsed":280252,"user":{"displayName":"all Penelitian","userId":"10978130364565931227"}},"outputId":"44374f1e-bc14-4c9c-efe9-c7575b9b4572"},"execution_count":9,"outputs":[{"output_type":"stream","name":"stdout","text":["Using 50000 samples for ANN (Price) evaluation.\n"]},{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.12/dist-packages/keras/src/layers/core/dense.py:106: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead.\n","  super().__init__(activity_regularizer=activity_regularizer, **kwargs)\n"]},{"output_type":"stream","name":"stdout","text":["\u001b[1m313/313\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step\n"]},{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.12/dist-packages/keras/src/layers/core/dense.py:106: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead.\n","  super().__init__(activity_regularizer=activity_regularizer, **kwargs)\n"]},{"output_type":"stream","name":"stdout","text":["\u001b[1m313/313\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step\n"]},{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.12/dist-packages/keras/src/layers/core/dense.py:106: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead.\n","  super().__init__(activity_regularizer=activity_regularizer, **kwargs)\n"]},{"output_type":"stream","name":"stdout","text":["\u001b[1m313/313\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 3ms/step\n"]},{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.12/dist-packages/keras/src/layers/core/dense.py:106: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead.\n","  super().__init__(activity_regularizer=activity_regularizer, **kwargs)\n"]},{"output_type":"stream","name":"stdout","text":["\u001b[1m313/313\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step\n"]},{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.12/dist-packages/keras/src/layers/core/dense.py:106: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead.\n","  super().__init__(activity_regularizer=activity_regularizer, **kwargs)\n"]},{"output_type":"stream","name":"stdout","text":["\u001b[1m313/313\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 3ms/step\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 3000x1800 with 1 Axes>"],"image/png":"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STABILITY SUMMARY (ANN PRICE) ---\n","Mean Accuracy: 0.9949\n","Std Dev: 0.0034\n","\n","Model dan Data Convergence (Accuracy) berhasil disimpan.\n"]}]},{"cell_type":"code","source":["\n","# Example prediction (replace with your actual data)\n","example_features = user_price_features[0]  # Example datapoint\n","prediction = (model.predict(np.array([example_features])) > 0.5).astype(\"int32\")\n","print(f\"Prediction for the example datapoint: {prediction}\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"FXgmBUNTWiOJ","executionInfo":{"status":"ok","timestamp":1734887544151,"user_tz":-420,"elapsed":379,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}},"outputId":"28a5c81c-e433-4a69-ef99-509a40fc8fe6"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 38ms/step\n","Prediction for the example datapoint: [[0]]\n"]}]},{"cell_type":"code","source":["import joblib\n","import pandas as pd\n","import numpy as np\n","import tensorflow as tf\n","from sklearn.model_selection import KFold\n","from sklearn.model_selection import train_test_split\n","from sklearn.metrics import accuracy_score, classification_report\n","\n","# Load the saved model\n","with open('/content/drive/MyDrive/Projects/Disertation/SOTA Bundle Matching/models/price_patterns/neural_networks_price_patterns.pkl', 'rb') as file:\n","    loaded_model = joblib.load(file)\n","\n","# Split data into training and testing sets\n","X_train, X_test, y_train, y_test = train_test_split(user_price_features, user_price_label, test_size=0.2, random_state=42)\n","\n","# Now you can use the loaded_model to make predictions\n","# For example:\n","y_pred = loaded_model.predict(X_test)\n","y_pred = (y_pred > 0.5).astype(int)  # Convert probabilities to binary predictions (0 or 1)\n","y_pred = y_pred.flatten() # Flatten y_pred to a 1D array\n","\n","print(classification_report(y_test, y_pred))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"FMRD6RqjGNbK","executionInfo":{"status":"ok","timestamp":1735051114521,"user_tz":-420,"elapsed":91190,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}},"outputId":"386467ef-11cc-48e9-dee6-d7ee94ca95d3"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["\u001b[1m37961/37961\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m57s\u001b[0m 2ms/step\n","              precision    recall  f1-score   support\n","\n","           0       1.00      1.00      1.00    602313\n","           1       1.00      1.00      1.00    612435\n","\n","    accuracy                           1.00   1214748\n","   macro avg       1.00      1.00      1.00   1214748\n","weighted avg       1.00      1.00      1.00   1214748\n","\n"]}]},{"cell_type":"code","source":["from google.colab import drive\n","drive.mount('/content/drive')"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"XfpLJxOdF79c","executionInfo":{"status":"ok","timestamp":1735050941077,"user_tz":-420,"elapsed":19421,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}},"outputId":"804fb55e-d0c2-4955-acf1-949a0e3e6594"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"]}]},{"cell_type":"markdown","source":["### Save"],"metadata":{"id":"h9g0gPIn7smF"}},{"cell_type":"code","source":["# prompt: save model best_mlp_classifier\n","\n","import joblib\n","\n","# Assuming neural_networks is defined as in your provided code.\n","# Assuming 'neural_networks' is your trained model\n","joblib.dump(model, '/content/drive/MyDrive/Projects/Disertation/SOTA Bundle Matching/models/price_patterns/neural_networks_price_patterns.pkl')\n","print(\"Model saved to neural_networks.pkl\")"],"metadata":{"id":"FoYSaGaJR1wo","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1734887466457,"user_tz":-420,"elapsed":9,"user":{"displayName":"Fundamental RecSys","userId":"12384593251438087944"}},"outputId":"3bf0e99e-5628-471d-cc09-85a630a08376"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Model saved to neural_networks.pkl\n"]}]},{"cell_type":"markdown","source":["### Predic Bundle"],"metadata":{"id":"unvcsZe_xUw-"}},{"cell_type":"code","source":[],"metadata":{"id":"6EVDa1hXxYv6"},"execution_count":null,"outputs":[]}]}
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